نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 کارشناس ارشد مخابرات، دانشکده مهندسی برق،دانشگاه یزد، یزد

2 دانشیار گروه مخابرات، دانشکده مهندسی برق،دانشگاه یزد، یزد

3 استادیار گروه مهندسی پزشکی، دانشکده فنی مهندسی، دانشگاه اصفهان، اصفهان

10.22041/ijbme.2015.19885

چکیده

سیستم‌های BCI مبتنی­بر SSVEP به­دلیل مزایایی چون سرعت انتقال اطلاعات بالا، نسبت بالای سیگنال به نویز و راحتی کاربران در استفاده از آن‌ها، توجه بسیاری از محققان را به خود جلب کرده­اند. هدف پردازشی در این سیستم‌ها، شناسایی فرکانس ظاهر­شده در سیگنال EEG کاربر است. از میان روش‌های پردازشی مختلفی که برای شناسایی فرکانس در سیستم‌های BCI مبتنی­بر SSVEP استفاده می­شوند، روش LASSO با استقبال فراوانی همراه بوده­است. باوجود عملکرد قابل­قبول روش LASSO در سیستم‌های BCI مبتنی­بر SSVEP، این روش در هنگام ساخت سیگنال مرجع، اختلاف فاز احتمالی بین سیگنال مرجع و سیگنال EEG ثبت­شده را درنظر نمی‌گیرد. در این مقاله، ایدة اصلاح فاز سیگنال مرجع با توجه به سیگنال EEG ثبت‌شده بررسی شده و روش پیشنهادی با عنوان LASSO با فاز تصحیح‌شده مطرح­شده است. در این مطالعه، ابتدا کانال مناسب برای شناسایی فرکانس در سیستم‌های BCI مبتنی­بر SSVEP انتخاب شد و در ادامه، مقایسه‌ای بین روش LASSO استاندارد و روش پیشنهادی LASSO با فاز تصحیح‌شده انجام شد. نتایج این مقاله نشان می‌دهد که اصلاح فاز سیگنال مرجع در روش پیشنهادی LASSO با فاز تصحیح‌شده، به بهبود نتایج شناسایی فرکانس نسبت به روش LASSO استاندارد منجر می‌شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Performance Evaluation of Phase Corrected LASSO Algorithm in SSVEP-Based BCI systems

نویسندگان [English]

  • Mohammad Ali Manouchehri 1
  • Vahid Abootalebi 2
  • Amin Mahnam 3

1 M.Sc. Graduate, Department of Electrical Engineering, Yazd University, Yazd, Iran

2 Associate Professor, Department of Electrical Engineering, Yazd University, Yazd, Iran

3 Assistant Professor of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran

چکیده [English]

SSVEP-based BCI systems have attracted attention of many researchers due to their high signal to noise ratio, high information transfer rate and being easy for use. The processing goal of these systems is to detect the stimulus frequency of EEG signal. Among the processing methods for frequency identification in SSVEP-based BCI systems, LASSO algorithm has gained great acceptance. Although LASSO has acceptable performance in SSVEP-based BCI systems, it doesn't consider the phase of recorded EEG signal for creating the reference signal. In this paper, the idea of correcting the phase of the reference signal with respect to recorded EEG signal was investigated and a new method called phase corrected LASSO was proposed. For this purpose, first, the optimal EEG channel for frequency identification was determined and then, the performance of the phase corrected LASSO method was compared with standard LASSO method. The results show that the phase corrected LASSO method has better performance compared with the standard LASSO method.

کلیدواژه‌ها [English]

  • Brain-Computer Interface (BCI)
  • Steady-State Visual Evoked Potential (SSVEP)
  • frequency identification
  • LASSO
  • Phase Corrected LASSO

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